Results for “ntlmssp”

Detect NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, and auditing SMB and LDAP signing enforcement.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency on NVIDIA GPUs (A100/H100).

Enumerate SMB, WinRM, LDAP, and MSSQL services, validate credentials, spray passwords, and execute commands on remote hosts using NetExec during authorized penetration tests.

Runs R statistics analyses on local datasets, producing NLSS-format tables, narratives, and JSONL logs from CSV, SAV, RDS, RData, or Parquet files.

Detect NTFS timestamp manipulation (MITRE T1070.006) by comparing $STANDARD_INFORMATION vs $FILE_NAME timestamps in the MFT using analyzeMFT and Python.

Runs NV-Segment-CTMR segmentation on CT or MRI NIfTI volumes and records label-map evidence.

Build, deploy, evaluate, debug, and measure latency for a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection and VLM classification.

Bootstraps a BSP customization workspace for NVIDIA Jetson, including the Linux_for_Tegra overlay tracker, bsp_sources mono-tree, and Crosstool-NG toolchain.

Copies overlay files and built artifacts into a staged BSP image for NVIDIA Jetson platforms, preparing it for flashing without modifying the workspace.

Downloads NVIDIA Jetson Linux BSP artifacts (BSP tarball, sample rootfs, public_sources, x-tools, guides) for the active target. Used for Auto Setup; does not extract or edit profiles.

Recommends an inference runtime and memory-related launch flags for LLM/VLM workloads on NVIDIA Jetson devices, based on a live memory audit snapshot.

Add, remove, edit, list, or change the boot default of nvpmodel power modes on Jetson/Tegra platforms (Orin, Thor) by modifying the BSP-side configuration file.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

Configures, troubleshoots, and extends NPSP Customizable Rollups, including rollup definitions, filter groups, batch job modes, and migration from legacy rollups.

Understand and query the NPSP data model, including namespace prefixes, GAU allocations, recurring donations, relationships, and affiliations.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

Performs advanced network reconnaissance using Nmap's scripting engine, timing controls, evasion techniques, and output parsing to discover hosts, enumerate services, detect vulnerabilities, and fingerprint operating systems across authorized target networks.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Program LM pipelines with DSPy — define Signatures (input/output fields), build Modules (ChainOfThought, ReAct, Predict), compose them into Programs, then optimize with Teleprompters (BootstrapFewShot, MIPRO, COPRO) to auto-improve prompts from examples.

Simulates SSL stripping attacks using sslstrip, Bettercap, and mitmproxy in authorized environments to test HSTS enforcement, certificate validation, and HTTPS upgrade mechanisms.

Simulates man-in-the-middle attacks using Ettercap, mitmproxy, and Bettercap in authorized environments to intercept, analyze, and modify network traffic for testing encryption enforcement, certificate validation, and detection capabilities.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming. Use when you need to build complex AI systems, program LMs declaratively, optimize prompts automatically, create modular AI pipelines, or build RAG systems and agents.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Guides the creation of high-quality MCP servers that let LLMs interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution on local Docker, Slurm HPC, or cloud platforms.

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Trigger machine account authentication with PetitPotam (MS-EFSR) and Coercer across MS-RPRN, MS-DFSNM, and MS-FSRVP to feed NTLM relay into AD CS Web Enrollment (ESC8) and other relay targets.

Internal network assessment. VLAN hopping, ARP spoofing detection, broadcast protocol abuse (LLMNR/NBT-NS/mDNS), network segmentation verification, SNMP enumeration, NFS exposure, router/switch audit, and internal service mapping. Assumes attacker has network access. Uses nmap, arp-scan, nbtscan, snmpwalk, onesixtyone, smbmap, nfs-common, masscan, hping3, and netexec.

Runs the NTM operator skill through Codex, using the local shell and returning concrete evidence of commands run and files touched.

NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.